An algorithm for maximizing target achievement in the stochastic knapsack problem with normal returns

We consider the stochastic linear knapsack problem in which costs are known with certainty but returns are independent, normally distributed random variables. The objective is to maximize the probability that the overall return equals or exceeds a specified target value. A previously proposed preference order dynamic programming-based algorithm has been shown to be potentially suboptimal. We offer an alternative hybrid DP/branch-and-bound algorithm that both guarantees optimality and significantly outperforms generating the set of Pareto optimal returns.© 1993 John Wiley & Sons, Inc.     

Polynomial‐time approximation schemes for two‐machine open shop scheduling with nonavailability constraints

This paper addresses a two‐machine open shop scheduling problem, in which the machines are not continuously available for processing. The processing of an operation affected by a non‐availability interval can be interrupted and resumed later. The objective is to minimize the makespan. We present two polynomial‐time approximation schemes, one of which handles the problem with one non‐availability interval on each machine and the other for the problem with several non‐availability intervals on one of the machines. Problems with a more general structure of the non‐availability intervals are not approximable in polynomial time within a constant factor, unless . © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Dynamic proximity calculations for situation awareness

We apply dynamic proximity calculations (density and clustering) from dynamic computational geometry to a military application. The derived proximity information serves as an abstract view of a current situation in the battlefield that can help a military commander achieve situation awareness. We employ Delaunay triangulation as a computational tool in our framework, and study its dynamic update in depth. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Entropy-based selection with multiple objectives

In this article we present an approach to determine the initially unspecified weights in an additive measurable multiattribute value function. We formulate and solve a series of nonlinear programming problems which (1) incorporate whatever partial information concerning the attribute weights or overall relative value of alternatives the decision maker chooses to provide, yet (2) yield a specific set of weights as a result. Although each formulation is rather easily solved using the nonlinear programming software GINO (general interactive optimizer), solutions in closed form dependent on a single parameter are also provided for a number of these problems.     

Military Interventions in Civil Wars: Protecting Foreign Direct Investments and the Defence Industry

ABSTRACT

This study extends existing scholarship on the influence of corporate/industry investments on the onset of military interventions in civil wars challenging prior null findings. It proposes a state-centric theoretical framework and argues that researchers have to differentiate between the protection and the advancement of corporate/industry interests. Random-effect logit models in combination with UCDP data on interventions from 2001 until 2009 corroborate the hypothesis that the protection of existing foreign direct investments, as well as the protection of prior arms trade, increase the willingness of a state to intervene militarily in a civil war.